The Forest Agent-Based
Landowner Economy (FABLE)
Jesse Henderson
Ph.D. Student
North Carolina State University
Two themes in the literature
1. Forest landowner decisions – (how to
determine optimal time to harvest given
what a landowner values)
2. Aggregate market behavior –
(characteristics of those that harvest,
supply elasticity, total harvests, price
changes)
Problem: what is the connection?
Individuals
?
Aggregate
Literature: forest landowner decisions





1
Classical Faustmann – cut at a certain age
Hartman – value on standing forest1
Reservation price – “the price is right”2
Landowner demographics/preferences3
Decisions with uncertain prices/risk4
(Hartman, 1976)
2 (McGough, Plantinga, & Provencher, 2004)
3 (Amacher, Conway, & Sullivan, 2003) (Binkley, 1981)
4 (Norstrom, 1975) (Routledge, 1980) (Koskela, 1989)
(Pukkala & Kanga, 1996) (Zhang, 2001)
Literature: landowner heterogeneity
SURVEYS & CLUSTER ANALYSES
- Timber, Multiobjective, Nontimber1 (National Woodland Owner Survey)
- Thoreau, Muir, Jane Doe3
- “Multiobjective, Recreationists, Self-employed owners, Investors, and
Indifferent owners”4
 Representing landowner behavior by group or type
(with variation) might better describe the situation.
1
(Majumdar, Teeter, & Butler, 2008)
2 (Finley & Kittredge, 2006)
3 (Favada, Karppinen, Kuuluvainen, Mikkola, & Stavness, 2009)
Literature: aggregating individuals
1. “Engineering” models
+
2. Econometric models1
=
3. Probit
models2
4. Agent-based models
1
(Wear & Parks, 1994)
2 (Prestemon & Wear, 2000)
x
Literature: agent-based modeling
 Features of agent-based modeling (Gilbert, 2006)
 A computational method
 Heterogeneous agents
 Representation of an environment
 Agent Interactions
 Bounded rationality
 Learning
 Previous applications
 Forest Economics: W. Canada, pine beetle risk (Schwab et al., 2009)
 Environ. Sci.: Harvesting/ecosystem services (Satake et al 2007)
 Artificial Markets (Schredelseker & Hauser, 2008)
Objectives - FABLE
• Develop an agent-based timber market
model which simulates inventory, removals
and prices which emerge from
heterogeneous agents.
• Determine the market features that result
from each of five cases.
• Determine the supply response to different
levels of demand and the implications for
sustainability.
Methods: bidding
D
P
S
Q
Bid heterogeneity from:
1. Heterogenous discount rates
2. Heterogeneous stand ages
Methods: outputs of the model
•
•
•
•
•
•
•
supply elasticity
sustainability index
price
average harvest age
removals
demand
inventory
𝑄𝑗 +1 − 𝑄𝑗
𝑃𝑗 +1
𝐸𝑠 =
∙
𝑄𝑗
𝑃𝑗 +2 − 𝑃𝑗 +1
2310
2300
2290
2280
2270
2260
2250
2240
2230
2220
2210
2200
2190
2180
2170
2160
2150
2140
2130
2120
2110
2100
2090
2080
2070
2060
2050
2040
2030
2020
2010
Inventory (Million Green Tons)
66% Reservation Price Faustmann:
inventory
6
5
4
8
3
14
2
20
1
0
Inventory for reservation price Faustmann (66%) and reservation
price Hartman (34%) by demand level
Remova ls (Thousa nd Green Tons)
66% Reservation Price Faustmann:
removals  demand
400
350
300
250
8
200
14
150
20
100
50
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2160
2170
2180
2190
2200
2210
2220
2230
2240
2250
2260
2270
2280
2290
2300
2310
0
Removals for reservation price Faustmann (66%) and reservation
price Hartman (34%) by demand level
66% Reservation Price Faustmann:
price
8
210
10
Price ($ / green ton)
12
14
160
16
18
20
110
60
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2160
2170
2180
2190
2200
2210
2220
2230
2240
2250
2260
2270
2280
2290
2300
2310
10
Price for reservation price Faustmann (66%) and reservation
price Hartman (34%) by demand level
66% Reservation Price Faustmann:
average harvest age
80
Average Harvest Age (years)
70
60
50
8
40
20
30
20
10
Harvest age for reservation price Faustmann (66%) and
reservation price Hartman (34%) by demand level
2200
2190
2180
2170
2160
2150
2140
2130
2120
2110
2100
2090
2080
2070
2060
2050
2040
2030
2020
2010
0
Results/Conclusion: supply curves
35
30
Price ($ / green ton)
25
20
Faustmann-R
Hartman-R
15
Faustmann 66%
Hartman 66%
10
5
0
90000
110000
130000
150000
170000
190000
210000
230000
Quantity (green tons)
Supply curves for four cases in the year 2020
Results/Conclusion: supply curves
120
Price ($ / green ton)
100
80
Faustmann-R
60
Hartman-R
Faustmann 66%
Hartman 66%
40
20
0
90000
100000
110000
120000
130000
140000
150000
Quantity (green tons)
Supply curves for four cases in the year 2060
Results/Conclusion: supply curves
70
60
Price ($ / green ton)
50
40
Faustmann-R
Hartman-R
30
Faustmann 66%
Hartman 66%
20
10
0
90000
100000
110000
120000
130000
140000
150000
Quantity (green tons)
Supply curves for four cases in the year 2250
2310
2300
2290
2280
2270
2260
2250
2240
2230
2220
2210
2200
2190
2180
2170
2160
2150
2140
2130
2120
2110
2100
2090
2080
2070
2060
2050
2040
2030
2020
2010
Price ($ / green ton)
200
120
50
100
40
80
30
60
20
40
20
10
0
0
Average Harvest Age (years)
Results/Conclusion:
Harvest age and Price Bubbles
80
20 - Price
180
70
20 - Average Harvest Age
160
60
140
2010
91+
81 to 90
71 to 80
61 to 70
51 to 60
41 to 50
31 to 40
21 to 30
11 to 20
0 to 10
Frequency
Results/Conclusion:
Age Class Histograms
1200
1000
800
600
400
200
0
2020
91+
81 to 90
71 to 80
61 to 70
51 to 60
41 to 50
31 to 40
21 to 30
11 to 20
0 to 10
Frequency
Results/Conclusion:
Age Class Histograms
1800
1600
1400
1200
1000
800
600
400
200
0
2040
91+
81 to 90
71 to 80
61 to 70
51 to 60
41 to 50
31 to 40
21 to 30
11 to 20
0 to 10
Frequency
Results/Conclusion:
Age Class Histograms
1600
1400
1200
1000
800
600
400
200
0
THANKS
Acknowledgements:
Bob Abt, Jeff Prestemon, Fred Cubbage
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